Image signal processing apparatus, imaging apparatus, image signal processing method and computer program

ABSTRACT

There is provided an image signal processing apparatus, comprising a demosaic processing unit receiving input of mosaic image data of each of signals obtained by a single plate imaging device having an element array composed of visible light obtaining elements obtaining visible light signals, and invisible light obtaining elements obtaining signals including invisible light components, and generating a demosaic image of each of the obtained signals; and a noise reduction processing unit receiving input of the demosaic image to execute correction of pixel values of the demosaic image obtained by the visible light obtaining elements on the basis of edge information extracted from the demosaic image of the signals obtained by the invisible light obtaining elements.

RELATED PATENT APPLICATIONS

This application is a continuation of and claims the benefit of priorityof U.S. patent application Ser. No. 11/640,244, filed Dec. 18, 2006 (nowallowed), which claims the benefit of priority to Japanese PatentApplication No. 2005-369378, filed Dec. 22, 2005, the entire contents ofwhich are both incorporated herein by reference to their entireties.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to an image signal processing apparatus,an imaging apparatus, an image signal processing method and a computerprogram, and more particularly to an image signal processing apparatus,an imaging apparatus, an image signal processing method and a computerprogram for performing signal processing of imaged data by a solid stateimaging device of a single plate color system.

2. Description of Related Art

A general solid state imaging device of the single plate color systemhas a color filter stuck thereto to transmit a specific wavelengthcomponent in each pixel to a surface of an imaging device, and restoresnecessary color components by a set of a plurality of pixels. At thistime, for example, a Bayer color array that expresses red (R), green (G)and blue (B) a set of four pixels as shown in FIG. 1 or the like is usedas the color array used for the color filter. Because each pixel hasonly the information of a single color component like this in the solidstate imaging device of the single plate color system, demosaicprocessing that restores necessary color components in each pixel byperforming interpolation processing using the color information ofsurrounding pixels is performed.

The configuration of an imaging apparatus equipped with a solid stateimaging device of the single plate color system is shown in FIG. 2. Asolid state imaging device 13 of the single plate color system receivesthe light that transmits a color filter 12 among the incident lightthrough an optical lens 11. An image signal that is photoelectricallyconverted by the solid state imaging device 13 to be output as anelectric signal is converted into a digital signal by a not shown A/Dconverter. After that, the converted image signal receives clippingprocessing, gamma correction, white balance correction, demosaicprocessing and the like in a camera signal processing unit 14, and theprocessed signal is transmitted to an image compressing unit 15. Theimage compressing unit 15 reduces the amount of data of the imagesignal, and converts the reduced image signal into a predeterminedrecording image format to output the converted image signal. A recordingunit 16 records the converted image data on a recording medium.Hereupon, it is not always necessary to perform the image compressingprocessing, the image compression is ordinarily performed because thenumber of pixels of an imaging device has increased in recent years andthe miniaturization of an apparatus itself has been required.

With reference to FIG. 3, the demosaic processing of an image obtainedby the solid state imaging device of a single plate color system isdescribed. The solid state imaging device of a single plate color systemis configured to perform imaging through a color filter having a colorarray such as the Bayer color array of the primary color system (seeFIG. 1) or the like, and is configured to obtain only the signals havinga specific wavelength to each pixel, i.e., the color component data of aspecific wavelength. In a case of using the solid state imaging deviceof the single plate color system having the Bayer color array, an outputimage 20 of the solid state imaging device becomes a color mosaic imagehaving only one piece of information of R, G and B at each pixel.

A demosaic processing unit 21 executes the processing of restoring allpieces of information of each color component data, i.e., R, G and B, byperforming color interpolation processing to each pixel.

First, the restoration of a G signal which restoration is executed bythe demosaic processing unit 21 is described. In the Bayer color array,the G signal is obtained in a checkered pattern. At a pixel at which noG signal exists in the output image 20 of the solid state imagingdevice, for example, a case of G₁₁, the G signal is generated byinterpolation processing based on surrounding G signals. To put itconcretely, the G signal (G₁₁) is restored in accordance with thefollowing expression.G ₁₁=(¼)(G ₀₁ +G ₂₁ +G ₁₀ G ₁₂)

Next, the restorations of an R signal and a B signal are described. Inthe Bayer color array, the data of both of the R and B exist every otherpixel line. For example, R signals exist but no B signals exist in thepixel line of the top rung of the output image 20 of the solid stateimaging device shown in FIG. 3. Moreover, B signals exist but no Rsignals exist in the second pixel line.

In a pixel line in which either data R or data B exists, the data R orthe data B is obtained every other pixel. In the case where an R signal(B signal) exists in the same line as that of a pixel at which a certainR signal (B signal) does not exist in the output image 20 of the solidstate imaging device, for example, cases of R₀₁ and B₁₂, interpolatedpixel values in the pixels in which the R and B signals do not exist onthe pixel line can be calculated by the following expressions, and the Rsignal (B signal) of each pixel can be restored.R ₀₁=(½)(R ₀₀ +R ₀₂)B ₁₂=(½)(B ₁₁ +B ₁₃)

In the case where R signals (B signals) exist in the same column, forexample, cases of R₁₀ and B₂₁, the interpolated pixel values at thepixels where certain R and B signals do not exist can be similarlycalculated in accordance with the following expressions, and the Rsignal (B signal) in each pixel is restored.R ₁₀=(½)(R ₀₀ +R ₂₀)B ₂₁=(½)(B ₁₁ +B ₃₁)

Moreover, in a case where no R signals (B signals) exist in both of thesame line and the same column, for example, cases of R₁₁ and B₂₂, theinterpolated pixel values in the pixels in which certain R and B signalsexist can be calculated by the following expressions, and the R signal(B signal) at each pixel is restored.R ₁₁=(¼)(R ₀₀ +R ₀₂ +R ₂₀ +R ₂₂)B ₂₂=(¼)(B ₁₁ +B ₁₃ +B ₃₁ +B ₃₃)

The demosaic processing unit 21 performs the color interpolationprocessing as mentioned above, and outputs R signals 22 r, G signals 22g and B signals 22 b to all pixels. It is noted that the aboveinterpolation processing is only one example, and any colorinterpolation processing using the correlations with the other colorsignals may be performed.

Various image processing methods for reducing noise to improve the imagequality of an imaging apparatus equipped with a solid state imagingdevice of a single plate color system have been proposed. For example,Georg Petschnigg Et al, “Digital Photography with Flash and No-FlashImage pairs,” acm Transaction on Graphics, Vol. 23, Number 3, pp.664-672, August 2004 (a non-patent document 1) discloses a technique ofphotographing a plurality of images having different spectralcharacteristics one after another and utilizing the plurality of imageshaving the different spectral characteristics to obtain an image inwhich noise is reduced. That is, the technique photographs the followingtwo kinds of images sequentially:

(a) images that have been photographed with spectral characteristicsnear to a target and include much noise, and

(b) images that have been photographed with spectral characteristicsthat severally include an invisible light or a different color not to benear to the target and include little noise.

Then, the technique utilizes the images having the plurality ofdifferent spectral characteristics to obtain an image having a correctcolor and little noise.

A configuration of noise reduction processing using a solid stateimaging device of a single plate color system using the algorithm shownby the related art technique is described with reference to FIG. 4. Theimaging device 30 is an imaging device of the Bayer color array of ageneral RGB array, which has been described above with reference to FIG.1.

A plurality of images A and B is photographed using the imaging device30, changing light sources. That is, the images A and B are as follows:

(the image A) an image that has been photographed with a spectralcharacteristic near to a target and include much noise, and

(the image B) an image that has been photographed with a spectralcharacteristic that includes an invisible light or a different color notto be near to the target and includes little noise.

The two mosaic images A and B are obtained by the photographingprocessing. The mosaic image A is dark and has much noise, but the colorof which is correct. The mosaic image B is bright and includes littlenoise, but the color of which is incorrect. Two images of a high noiseimage A and a low noise image B are obtained by applying white balanceprocessing of correcting pixel values to each spectrum to thephotographed images A and B in white balance processing units 31 a and31 b, respectively, and by executing demosaic processing to the imageshaving been subjected to the white balance processing that has beendescribed with reference to FIG. 3 in demosaic processing units 32 a and32 b, respectively.

Moreover, the two images of the high noise image A and the low noiseimage B are input into a noise reduction processing unit 33, and thenoise reduction processing based on these two images is executed. Then,an output RGB image is obtained.

The configuration and the processing of the noise reduction processingunit 33 are described with reference to FIG. 5. The noise reductionprocessing unit 33 uses the two images of the high noise image A and thelow noise image B to produce the output RGB image, which has a colorequal to the high noise image A with reduced noise by synthesizing theseimages.

An RGB low pass filter 42 is a cross bilateral filter, which is a kindof an edge preserving filter, and reduces the noise of the high noiseimage A with the edges of the image A, which has much noise, beingpreserved on the basis of the edges detected from the respective R, Gand B components of the low noise image B as an input image.

An RGB low pass filter 41 applies a general FIR low pass filter, whichis not especially equipped with any edge preserving functions, to eachchannel of R, G and B. An RGB high pass filter 45 obtains the highfrequency component of each pixel value of R, G and B of the low noiseimage B, which is an input image having little noise. The acquisition ofthe high frequency components is performed by dividing the pixel valuesas the result of the application of the bilateral filter to the inputimages by the pixel values of the images before the application of thefilter.

A blend executing unit 44 applies a previously set blend function togenerate the image data having the pixel values obtained by multiplyingthe pixel values of an output image of the RGB low pass filter 42 by thepixel values of an output image of the RGB high pass filter 45, and tooutput the generated image data.

A speculum detecting unit 43 extracts the differences of the highlight,the shadow and the like in each pixel of the high noise image A and thelow noise image B owing to the illumination change between the twoimages, and evaluates the height of the possibility of the occurrence ofthe differences of pixel values owing to the illumination change. Ablend executing unit 46 performs the weighted addition of an output ofthe RGB low pass filter 41 and an output of the blend executing unit 44on the basis of an evaluation result of the speculum detecting unit 43to generate the output RGB image.

The blend executing unit 46 performs the setting of enlarging the weightof the pixel values output from the RGB low pass filter 41 in a pixelportion to which the speculum detecting unit 43 has judged that thepossibility of the occurrence of the shadow or the highlight owing tothe illumination change is high, and enlarging the weight of the pixelvalues output from the blend executing unit 44 in a pixel portion towhich the speculum detecting unit 43 has judged that the possibility ofthe occurrence of the shadow or the highlight owing to the illuminationchange is low by regarding the pixel portion as the appearance of thedetailed parts of a subject owing to the difference of illuminations.Thereby, the blend executing unit 46 performs the weighted addition ofthe output of the RGB low pass filter 41 and the output of the blendexecuting unit 44 to generate the output RGB image.

However, the algorithm is realized on the assumption that a plurality ofimages is photographed with different spectra, and consequently has aproblem of the impossibility of applying the algorithm to a generaldigital camera and a movie camera, which can photograph an image onlyonce at the same instant.

SUMMARY OF THE INVENTION

Consequently, there are a need to provide an image processing method forreducing noise to improve image quality of an image in an imagingapparatus equipped with a solid state imaging device of the single platecolor system, and a need to provide an image signal processingapparatus, an imaging apparatus, an image signal processing method and acomputer program all of which can exclude the necessity of inputting aplurality of images to reduce noise on the basis of a photographed imageand make it possible to obtain an output image having an improved imagequality.

Moreover, there is also a need to provide an image signal processingapparatus, an imaging apparatus, an image signal processing method and acomputer program all of which make it possible to realize noisereduction processing based on only a once photographed image by using animaging device (imager) that is set to have spectrum in an invisiblelight region in a part of a solid state imaging device of the singleplate color system, and which can be applied to a general digital stillcamera, a general video camera and the like.

A first aspect of the present invention is an image signal processingapparatus, including a demosaic processing unit and a noise reductionprocessing unit. The demosaic processing unit receives input of mosaicimage data of each of signals obtained by a single plate imager havingan element array composed of visible light obtaining elements obtainingvisible light signals, and invisible light obtaining elements obtainingsignals including invisible light components, and generates a demosaicimage of each of the obtained signals. The noise reduction processingunit receives input of the demosaic image to execute correction of pixelvalues of the demosaic image obtained by the visible light obtainingelements on the basis of edge information extracted from the demosaicimage of the signals obtained by the invisible light obtaining elements.

Moreover, in an embodiment of the image signal processing apparatus ofthe present invention, the visible light obtaining elements are RGBelements obtaining R, G and B color signals severally, and the invisiblelight obtaining elements are A elements obtaining A signals including R,G and B color signal components and infrared components. Furthermore,the demosaic processing unit is configured to receive input of mosaicimage data of each of the R, G, B and A signals obtained by the singleplate imager having a color array composed of the RGB elements obtainingthe R, G and B color signals severally, and the A elements obtaining theA signal including the R, G and B color signal components and theinfrared components, and to generate the demosaic image of each of theR, G, B and A signals. The noise reduction processing unit is configuredto receive input of the demosaic image of each of the R, G, B and Asignals, and to execute the correction of the pixel values of the RGBdemosaic image based on the edge information extracted from the demosaicimage of the A signal.

Moreover, in an embodiment of the image signal processing apparatus ofthe present invention, the noise reduction processing unit is configuredto execute processing of correcting the pixel values of the pixelsconstituting the RGB demosaic image on the basis of pixel values ofsurrounding pixels according to edge distribution near the pixels.

Moreover, in an embodiment of the image signal processing apparatus ofthe present invention, the image signal processing apparatus isconfigured such that the second demosaic processing unit generates anedge evaluating image as the demosaic image of the A signal, and thenoise reduction processing unit executes the demosaic processing of themosaic image of each of the R, G and B signals by collectively executingnoise reduction and demosaic processing by executing the demosaicprocessing in consideration of edge positions based on the edgeevaluating image as the demosaic image of the A signal.

Moreover, in an embodiment of the image signal processing apparatus ofthe present invention, the noise reduction processing unit is configuredto execute processing of calculating an output pixel value [Out(x, y)]of each pixel position (x, y) in the RGB mosaic image on the basis ofthe pixel values of the surrounding pixels by applying weight [W]calculated by a product of space-dependent weight [Ws] dependent upon adistance between a pixel of a correction object and a reference pixeland edge-dependent weight [Wr] dependent upon strength of an edge of animage calculated in conformity to the edge evaluating image as thedemosaic image of the A signal at a time of the demosaic processing ofthe mosaic images of each of the R, G and B signals.

Moreover, in an embodiment of the image signal processing apparatus ofthe present invention, the image signal processing apparatus furtherincludes an A-noise reduction processing unit and a matrix operationexecuting unit. The A-noise reduction processing unit generates anoise-reduced A demosaic image corresponding to the A signal on thebasis of the edge information extracted from the demosaic image of the Asignal. The matrix operation executing unit receives input of thenoise-reduced RGB demosaic image generated by the noise reductionprocessing unit and the noise-reduced A demosaic image, and convertspixel values of corresponding pixels of input four demosaic images of R,G, B and A by a matrix operation to generate the RGB image in which theinfrared components are removed form the R, G and B signals.

Moreover, in an embodiment of the image signal processing apparatus ofthe present invention, the matrix operation executing unit is configuredto generate and output an estimated infrared image composed of infraredcomponents on the basis of the noise-reduced RGB demosaic imagegenerated by the noise reduction processing unit and the noise-reduced Ademosaic image.

Moreover, a second aspect of the present invention is an imagingapparatus which includes an imager, a demosaic processing unit and anoise reduction processing unit. The imager has a color array composedof RGB elements obtaining R, G and B color signals severally and Aelements obtaining A signals including R, G and B color signalcomponents and infrared components. The demosaic processing unitreceives input of mosaic image data of each of the R, G, B and A signalsobtained by the single plate imager to generate a demosaic image of theR, G, B and A signals. The noise reduction processing unit receives theinput of the demosaic image of the R, G, B and A signals to correctpixel values of the RGB demosaic image on the basis of edge informationextracted from the demosaic image of the A signal.

Moreover, in an embodiment of the imaging apparatus of the presentinvention, the imager is configured to have a checker-patternarrangement of the A elements obtaining the A signals.

Moreover, a third aspect of the present invention is an image signalprocessing method including a demosaic processing step and a noisereduction processing step. The demosaic processing step is a step ofreceiving input of mosaic image data of each of signals obtained by asingle plate imager having an element array composed of visible lightobtaining elements obtaining visible light signals and invisible lightobtaining elements obtaining signals including invisible lightcomponents to generate a demosaic image of each of the obtained signals.The noise reduction processing step is a step of receiving input of thedemosaic image to execute a correction of pixel values of the demosaicimage obtained by the visible light obtaining elements based on edgeinformation extracted from the demosaic image of the signals obtained bythe invisible light obtaining elements.

Moreover, in an embodiment of the image signal processing method of thepresent invention, the visible light obtaining elements are RGB elementsobtaining R, G and B color signals severally, the invisible lightobtaining elements are A elements obtaining A signals including R, G andB color signal components and infrared components, the demosaicprocessing step is a step of receiving the input of the mosaic imagedata of each of the R, G, B and A signals obtained by the single plateimager having a color array composed of the RGB elements obtaining theR, G and B color signals severally, and the A elements obtaining the Asignals including the R, G and B color signal components and theinfrared components, and generating the demosaic image of each of the R,G, B and A signals, and the noise reduction processing step is a step ofreceiving the input of the demosaic image of each of the G, B and Asignals, and executing the correction of the pixel values of the RGBdemosaic image based on the edge information extracted from the demosaicimage of the A signals.

Moreover, in an embodiment of the image signal processing method of thepresent invention, the noise reduction processing step is a step ofexecuting processing of correcting the pixel values of the pixelsconstituting the RGB demosaic image on the basis of pixel values ofsurrounding pixels according to edge distribution near the pixels on thebasis of the edge information detected from the demosaic image of the Asignals.

Moreover, in an embodiment of the image signal processing method of thepresent invention, in the image signal processing method, the demosaicprocessing step is a step of generating an edge evaluating image as thedemosaic image of the A signals, and the noise reduction processing stepis a step of executing the demosaic processing of the mosaic image ofeach of the R, G and B signals by collectively executing noise reductionand demosaic processing by executing the demosaic processing la inconsideration of edge positions based on the edge evaluating image asthe demosaic image of the A signals.

Moreover, in an embodiment of the image signal processing method of thepresent invention, the noise reduction processing step is a step ofexecuting processing of calculating an output pixel value [Out(x, y)] ofeach pixel position (x, y) in the RGB demosaic image based on the pixelvalues of the surrounding pixels by applying weight [W] calculated by aproduct of space dependent weight [Ws] dependent upon a distance betweena pixel of a correction object and a reference pixel and edge-dependentweight dependent upon strength of an edge of an image calculated [Wr] inconformity to the edge evaluating image as the demosaic image of the Asignals at a time of the demosaic processing of the mosaic images ofeach of the R, G and B signals.

Moreover, in an embodiment of the image signal processing method of thepresent invention, the image signal processing method further includesan A-noise reduction processing step and a matrix operation executingstep. The A-noise reduction processing step is a step of generating anoise-reduced A demosaic image corresponding to the A signals on thebasis of the edge information extracted from the demosaic image of the Asignals. The matrix operation executing step is a step of receivinginput of the noise-reduced RGB demosaic image generated at the step ofreceiving the input of the demosaic image and the noise-reduced Ademosaic image, and converting pixel values of corresponding pixels ofinput four demosaic images of R, G, B and A by a matrix operation togenerate the RGB image in which the infrared components are removed fromthe R, G and B signals.

Moreover, in an embodiment of the image signal processing method of thepresent invention, the matrix operation executing step is a step ofgenerating and outputting an estimated infrared image composed of theinfrared components based on the noise-reduced RGB demosaic imagegenerated at the step of receiving the input of the demosaic image andthe noise-reduced A demosaic image.

Moreover, a fourth aspect of the present invention is a computer programfor making an imaging apparatus execute image signal processing, theprogram making the apparatus execute a demosaic processing step and anoise reduction processing step. The demosaic processing step is a stepof receiving input of mosaic image data of each of signals obtained by asingle plate imager having an element array composed of visible lightobtaining elements obtaining visible light signals and invisible lightobtaining elements obtaining signals including invisible lightcomponents to generate a demosaic image of each of the obtained signal.The noise reduction processing step is a step of receiving input of thedemosaic image to execute a correction of pixel values of the demosaicimage obtained by the visible light obtaining elements on the basis ofedge information extracted from the demosaic image obtained by theinvisible light obtaining elements.

It is noted that the computer program of the present invention is acomputer program capable of being provided by a storage medium such as aCD, an FD, an MO and the like, and a communication medium such as anetwork and the like, which are provided in a computer-readable form to,for example, a general purpose computer capable of executing variousprogram codes. By providing such a program in the computer-readableform, the processing corresponding to the program can be realized on thecomputer system.

Further features and advantages of the present invention will becomeapparent from the following description of exemplary embodiments of thepresent invention with reference to the attached drawings. In addition,a system in the present specification means the configuration of alogical set of a plurality of apparatus, and is not limited to the onein which the apparatus of each configuration is located in the samehousing.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram for describing an example of the Bayer color arrayas a color array used for a general color filter;

FIG. 2 is a diagram showing a configuration of an imaging apparatusequipped with a solid state imager of a single plate color system;

FIG. 3 is a diagram for describing demosaic processing;

FIG. 4 is a diagram describing a signal processing example of aphotographed image in a related art;

FIG. 5 is a diagram describing the signal processing example of thephotographed image in the related art;

FIG. 6 is a diagram for describing the color array of an imager to whichthe present invention is applied;

FIG. 7 is a diagram describing an image signal processing configuration(a first processing example) according to an embodiment of the presentinvention;

FIGS. 8A and 8B are diagrams for describing a mosaic image and ademosaic image that are generated in the processing of the presentinvention;

FIG. 9 is a diagram describing a configuration of a noise reductionprocessing unit in the image signal processing configuration (the firstprocessing) according to the embodiment of the present invention;

FIG. 10 is a diagram describing an image signal processing configuration(a second processing example) according to the embodiment of the presentinvention;

FIG. 11 is a diagram describing the configuration of a demosaic andnoise reduction processing unit in the image signal processingconfiguration (the Second processing example) according to theembodiment of the present invention;

FIG. 12 is a diagram for describing the processing of a demosaic andnoise reduction filter in the image signal processing configuration (thesecond processing example) according to the embodiment of the presentinvention;

FIG. 13 is a diagram for describing the factors of a FIT high passfilter in the image signal processing configuration (the secondprocessing example) according to the embodiment of the presentinvention;

FIG. 14 is a diagram describing an image signal processing configuration(a third processing example) according to the embodiment of the presentinvention;

FIG. 15 is a diagram describing an image signal processing configuration(a fourth processing example) according to the embodiment of the presentinvention; and

FIG. 16 is a diagram describing the configuration of a demosaic & noisereduction & infrared (IR) calculation processing unit in the imagesignal processing configuration (the fourth processing example)according to the embodiment of the present invention.

DETAILED DESCRIPTION OF THE EMBODIMENTS

In the following, a description will be given to an image signalprocessing apparatus, an imaging apparatus, an image signal processingmethod and a computer program of the present invention with reference tothe attached drawings. The description will be performed in thefollowing order:

-   -   1. configuration of imager    -   2. first image signal processing example    -   3. second image signal processing example    -   4. third image signal processing example    -   5. fourth image signal processing example        [1. Configuration of Imager]

First, a description will be given to the configuration of an imagingdevice (hereinafter, referred to as imager) applied to an imagingapparatus of the present invention. The imaging apparatus of the presentinvention has a configuration that is basically similar to the onedescribed above with reference to FIG. 2, but the imager applied to theimaging apparatus has a configuration different from the Bayer colorarray described with reference to FIG. 1. The configuration of theimager applied to the imaging apparatus of the present invention isdescribed with reference to FIG. 6. The general solid state imager ofthe single plate color system has been described above with reference toFIG. 1. The general solid state imager of the single plate color systemhas stuck thereto a color filter transmitting only a specific wavelengthcomponent in each pixel to the surface of the imager, and restoresnecessary color components by a set of a plurality of pixels. In thiscase, the Bayer color array expressing red (R), green (G) and blue (B)by means of a set of four pixels as shown in FIG. 1, for example, isused as the color array used in the color filter.

The imager applied to the imaging apparatus of the present inventionincludes a color array shown in FIG. 6. That is, the imager is composedof a color filter including the following four kinds of spectralcharacteristics: red (R) transmitting the wavelengths near a red color,green (G) transmitting the wavelengths near a green color, blue (B)transmitting the wavelengths near a blue color, and A transmitting allof the infrared rays (IR), R, G and B in addition to the former threecolors. The four kinds of spectra are composed of an R channel, a Gchannel, a B channel and an A channel transmitting all of the infraredrays (IR), the R, the G and the B, and a mosaic image composed of thefour kinds of spectra can be obtained by means of the imager.

The imager applied to the imaging apparatus of the present invention isa single plate imager including a color array composed of RGB elementsthat severally obtain R, G and B color signals, and A-elements thatobtain A-signals including R, G and B color signal components andinfrared components, as shown in FIG. 6. The A-signal obtaining elementsare arranged in a checkered pattern. The imaging apparatus of thepresent invention executes signal processing such as the noise reductionprocessing, the infrared light removing processing and the like of dataof an image photographed by applying the imager shown in FIG. 6 toobtain a high quality image.

[2. First Image Signal Processing Example]

Next, a first specific example of the noise reduction processing of thedata of the image photographed by the application of the imager shown inFIG. 6 is described with reference to FIG. 7 and so forth. The presentprocessing example is a processing example of executing the noisereduction processing of an image including much noise, such as an imagephotographed at a low illumination, on the basis of the data of theimage photographed by applying the imaging device (imager) shown in FIG.6.

FIG. 7 shows the image signal processing configuration of an imagingapparatus according to a first embodiment of the present invention. Animager 101 is the imager of R, G, B and A described with reference toFIG. 6, and includes a filter having a spectral characteristic of thefour kinds of colors of R, G, B and A. The four kinds of spectra arecomposed of the R channel, the C channel, the B channel and the Achannel transmitting all of infrared rays (IR), R, G and B.

An image photographed by the imager 101 becomes a mosaic image composedof the four kinds of spectra. The mosaic image is one composed of fourkinds of mosaic images composed of each channel of R, G, B and A asshown in FIG. 6A. These mosaic images are input into a white balanceprocessing unit 102.

The white balance processing unit 102 executes white balance correctingprocessing for making the ranges of the pixel values included in themosaic images having the four kinds of different spectralcharacteristics be almost the same. The correction of equalizing theranges of the values of the pixels included in each of the mosaic imageshaving different spectral characteristics from one another to be almostthe same is performed to the values of the pixels constituting themosaic images by the white balance adjusting processing, and correctedmosaic images are obtained.

The arrays of the pixels of the four mosaic images are as shown in FIG.8A. In addition, as described above with reference to FIG. 6, the marksof R, G and B indicate the existence of the principal spectra of red,green and blue, respectively, and a pixel of A indicates a pixel thespectrum of which includes also an infrared ray (IR) component inaddition to blue, green and red.

The demosaic processing of these four mosaic images is executed at ademosaic processing unit 103, subsequently, and an RGB demosaic image111 and an A demosaic image 112 are obtained. The demosaic processing isperformed by the processing of setting the pixel values of all thepixels having no pixel values by executing the interpolation based onthe pixel values of the surrounding pixels, as described above withreference to FIG. 3. For example, a method similar to the well knownVargra algorithm can be applied. The Vargra algorithm is an algorithmthat performs the demosaic processing by obtaining the gradients ofpixel values in eight directions to average the pixel values thegradients of which are close to one another.

By the demosaic processing in the demosaic processing unit 103, fourdemosaic images shown in FIG. 8B can be obtained. The upper threedemosaic images correspond to the RGB demosaic image 111. The R, G and Bin the four demosaic images shown in FIG. 8B denote the pixel valuesobtained by the mosaic images, and r, g and b denote interpolated pixelvalues obtained by the demosaic processing. The bottom rung of FIG. 8Bshows a demosaic image A obtained from the mosaic image of the A channeltransmitting all of infrared rays (IR), R, G and B. A mark A denotes apixel value obtained from the mosaic image, and a mark a denotes aninterpolated pixel value obtained by the demosaic processing.

The RGB demosaic image 111 and the A demosaic image 112 that have beenobtained in such a way are input into a noise reduction processing unit104, and noise reduction processing is executed to obtain an output RGBimage.

The configuration and the processing of the noise reduction processingunit 104 are described with reference to FIG. 9. The noise reductionprocessing unit 104 receives the input of the two demosaic imagesgenerated on the basis of one photographed image, i.e. the RGB demosaicimage 111 and the A demosaic image 112, and produces an image the noiseof which has been reduced by the synthesization of these images, i.e.,the output RGB image.

The configuration of the noise reduction processing unit 104 shown inFIG. 9 is a configuration similar to that of the noise reductionprocessing unit 33 described above with reference to FIG. 5. In theexample of the configuration described above, the noise reductionprocessing has been executed on the basis of the two images photographedat different timings:

(a) a high noise image photographed with a spectral characteristic nearto a target spectral characteristic, and

(b) a low noise image photographed with a spectral characteristic thatincludes an invisible light or has a different color not to be near tothe target spectral characteristic. However, in the present embodiment,an image the noise of which is reduced, i.e., the output RGB image, isgenerated on the basis of the images obtained by one time ofphotographing processing:

(a) the RGB demosaic image 111, and

(b) the A demosaic image 112.

The noise reduction processing unit 104 of the present embodimentperforms the processing of effectively reducing the noise included inthe RGB demosaic image 111 on the basis of the A demosaic image 112 as alow noise image. An RGB low pass filter 122 is a cross bilateral filteras a kind of the edge preserving filter, and reduces the noise whilepreserving the edges included in the RGB demosaic image 111, which is aninput image including much noise, on the basis of the edges detectedfrom the A components of the A demosaic image 112 as an input image.

The RGB low pass filter 122 executes the correction of the pixel valuesof the RGB demosaic image 111 on the basis of the edge portions detectedfrom the A components of the A demosaic image 112. Specifically, theprocessing of the filter 122 is a processing of correcting the pixelvalue of the pixel of the correction object on the basis of surroundingpixels thereof, by judging whether or not any edges exist near the pixelwhose pixel value is to be corrected on the basis of the edgeinformation detected from the A components of the A demosaic image 112,and by setting the weight of the pixel values of the pixels in thedirections in which no edge portions exist large and the weight of thepixel values of the pixels in the directions in which the edge portionsexist small. The reduction of the noise of the RGB demosaic image 111can be contrived by the processing.

The RGB demosaic image 111 includes three RGB demosaic images as shownin FIG. 8B, and the noise of all of the three RGB demosaic images isreduced on the basis of the edges detected from the A components of theA demosaic image 112 while preserving the edges included in the RGBdemosaic image 111.

An RGB low pass filter 121 includes general FIR low pass filters each ofwhich is not especially equipped with the edge preserving function andis applied to each channel of R, G and B. An A-high pass filter 125obtains the high frequency components of each of the A-pixel values ofthe A-demosaic image 112, which is an input image including littlenoise. The acquisition of the high frequency components is performed bydividing the pixel values of a result of the application of thebilateral filter to an input image by the pixel values of the imagebefore the application of the filter.

A blend executing unit 124 generates the image data having the pixelvalues obtained by multiplying the pixel values of an output image ofthe RGB low pass filter 122 by the pixel values of an output image ofthe A-high pass filter 125 by applying a previously set blend function,and outputs the generated image data.

A speculum detecting unit 123 extracts the differences such as ahighlight, a shadow and the like of each pixel of the two images of theRGB demosaic image 111 as the high noise image and the A-demosaic image112 as the low noise image, and evaluates the possibility of theoccurrence of the differences of the pixel values owing to theinfluences of the highlight, the shadow and the like. A blend executingunit 126 performs the weighted addition of an output, of the RGB lowpass filter 121 and an output of the blend executing unit 124 on thebasis of an evaluation result of the speculum detecting unit 123 togenerate the output RGB image.

The blend executing unit 126 performs the setting of enlarging theweight of the pixel values output from the RGB low pass filter 121 inthe pixel portions in which the possibility of the occurrence of thehighlight and the shadow is judged to be high by the speculum detectingunit 123, and of enlarging the weight of the pixel values output fromthe blend executing unit 124 by considering that detailed parts of asubject has appeared owing to the highlight and the shadow when thepossibility is low. The blend executing unit 126 thus performs theweighted addition of the output of the RGB low pass filter 121 and theoutput of the blend executing unit 124 to generate the output RGB image.

According to the processing example, the two images of (a) the RGBdemosaic image 111 and (b) the A demosaic image 112 are obtained by onetime of photographing processing, and the reduction of noise can beperformed on the basis of the obtained images. Consequently, it ispossible to apply the processing example to for example, a generaldigital camera and a general movie camera that can photograph an imageonly once at the same time, and it is possible even for such generalcameras to generate and obtain a high quality image with reduced noise.That is, it is possible to obtain an RGB output image that has accuratecolors and includes little noise by using an RGB demosaic image as aninput image having accurate colors and much noise and by using anA-demosaic image as an input image that has not correct colors but isbright and has little noise to perform the adjustment of the RGBdemosaic image on the basis of the edge data obtained from the Ademosaic image.

[3. Second Image Signal Processing Example]

Next, a second image signal processing example of the present inventionis described with reference to FIGS. 10-13. In the processingconfiguration, shown in FIG. 10, the processing up to obtaining a mosaicimage 211 including four mosaic images of R, G, B and A is similar tothat of the first processing example described above with reference toFIG. 7. That is, an imager 201 is the imager of R, G, B and A, which hasbeen described with reference to FIG. 6, and is composed of a filterhaving four kinds of spectral characteristics of R, G, B and A. The fourkinds of spectra are composed of an R channel, a G channel, a B channel,and an A channel transmitting all of the infrared rays (IR), the R, theG and the B.

An image photographed by the imager 201 becomes a mosaic image composedof the four kinds of the spectra. The mosaic image includes four kindsof the mosaic images composed of each channel of R, G, B and A, as shownin FIG. 8A. These mosaic images are input into a white balanceprocessing unit 202.

The white balance processing unit 202 executes the white balancecorrecting processing in order to equalize the ranges of the pixelvalues included in the mosaic images having the four kinds of differentspectral characteristics to be almost the same. The corrections ofequalizing the ranges of the pixel values included in each of the mosaicimages having different spectral characteristics from one another to bealmost the same by the white balance adjusting processing are performedto the values of the pixels constituting the mosaic images, and thecorrected mosaic images are obtained. The arrays of the pixels of thefour mosaic images are as shown in FIG. 8A.

In the present second processing example, the mosaic image (including R,G, B and A) 211 is input, into a demosaic & noise reduction processingunit 204, and the demosaic & noise reduction processing unit 204executes demosaic processing and noise reduction processing to obtain anoutput RGB image.

The configuration and the processing of the demosaic & noise reductionprocessing unit 204 are described with reference to FIG. 11. A lineardemosaic filter 225 receives the input of the mosaic image A includingthe R, G and B and infrared ray (IR) components in the mosaic image(including R, G, B and A) 211, and performs the demosaic processing ofthe mosaic image A by linear interpolating processing to obtain ademosaic image of the A-channel. The A-channel demosaic image is used asa monochrome edge evaluating image 212.

Demosaic and noise reduction filters 221, 222 and 223 perform the imageprocessing by edge preserving filters for reducing noise with the edgesof an original image, which are located at the same places as thoseappearing in the edge evaluating image 212, being preserved to themosaic images of R, G and B included in the mosaic image (including R,G, B and A) 211, which is an corrected mosaic image, respectively, andexecute demosaic processing. The demosaic processing is performed by theprocessing of setting the pixel values of all the pixels by executingthe interpolation based on the pixel values of the surrounding pixels tothe pixels having no pixel values, as described above with reference toFIG. 3. For example, a method similar to the well-known Vargra algorithmcan be applied.

The pixel value calculating processing in the demosaic and noisereduction filters 221, 222 and 223 is described. The demosaic and noisereduction filters 221, 222 and 223 generate the demosaic images thathave received noise reductions of R, G and B on the basis of input R, Gand B mosaic images, respectively. The processing is basically theprocessing of calculating a demosaic image from a mosaic image, whichhas been described above with reference to FIG. 8B. In the presentprocessing example, the edge evaluating image 212, which is based on anA-channel image and is shown in FIG. 11, is applied, and noise reductionis also executed at the time of the processing.

The basic processing in the demosaic and noise reduction filters 221,222 and 223 is described with reference to FIG. 12. For example, in acase where the pixel value at a pixel position (x, y) is calculated, theprocessing of calculating the pixel value is executed on the basis ofthe surrounding pixels. It is noted that the image is a mosaic image,and there are positions where pixel values exist and positions where nopixel values exist.

It is supposed that the pixel position of a surrounding pixel is denotedby (px, py), and the pixel value at the pixel position (x, y) iscalculated on the basis of the pixel values at a plurality ofsurrounding pixels (px, py). For example, the pixel value at the pixelposition (x, y) is determined on the basis of 7×7 pixels surrounding thepixel position (x, y). At the time of the pixel value determiningprocessing, predetermined weighting is executed to the values of thesurrounding pixels.

That is, the predetermined weighting is performed to the 7×7 pixelssurrounding the pixel position (x, y), and the output pixel value[Out(x, y)] of the pixel position (x, y) is determined by integratingthe results of multiplying the pixel values of the surrounding 7×7pixels by the weight W in consideration of the weight W. In a generaldemosaic processing, the weights [W] of the surrounding pixels are setto be larger to the pixels nearer to the pixel position (x, y), and areset to be smaller to the pixels farther from the pixel position (x, y).Thereby, the so-called space-dependent weight [Ws] is, set.

The present processing example of the present invention also applies theweight dependent upon the strength of edges, i.e., edge-dependentweights [Wr], collectively in consideration of the differences betweenthe pixel value of the pixel position (x, y) and the pixel values of thesurrounding pixel positions (px, py) in addition to the space-dependentweight [Ws]. The pixel value difference weight [Wr] is calculated fromthe edge evaluating image 212 based on the A-channel image shown in FIG.11, and both of the demosaic processing and the noise reductionprocessing can be collectively executed by the processing.

The calculation of the weight (1611 in consideration of thespace-dependent weight Ws and the edge-dependent weight [Wr], and thecalculation processing of the output pixel value [Out(x, y)] at thepixel position (x, y) are executed in conformity to the followingexpressions:

$\begin{matrix}{{W( {x,y,{px},{py}} )} = {{W_{r}( {x,y,{px},{py}} )} \cdot {W_{r}( {x,y,{px},{py}} )}}} & (1) \\{{W_{r}( {x,y,{px},{py}} )} = {\exp( {- \frac{( {x - {px}} )^{2} + ( {y - {py}} )^{2}}{2\sigma_{r}^{2}}} )}} & (2) \\{{W_{r}( {x,y,{px},{py}} )} = \lbrack {\exp( {- \frac{( {{{Edge}\;( {x,y} )} - {{Edge}\;( {{px},{py}} )}} )^{2}}{2\sigma_{r}^{2}}} )} \rbrack_{{if}\mspace{14mu}{({{{In}{({{px},{py}})}}{exists}})}}} & ( {3a} ) \\{{W_{r}( {x,y,{px},{py}} )} = \lbrack 0\rbrack_{{if}\mspace{11mu}{({{{In}{({{px},{py}})}}{{doesn}'}t\;{exist}})}}} & ( {3b} ) \\{{{Out}( {x,y} )} = \frac{\sum\limits_{{px} = {x - n}}^{x + n}\;{\sum\limits_{{py} = {y - n}}^{y + n}\;{{W( {x,y,{px},{py}} )} \cdot {{In}( {{px},{py}} )}}}}{\sum\limits_{{px} = {x - n}}^{x + n}\;{\sum\limits_{{py} = {y - n}}^{y + n}\;{W( {x,y,{px},{py}} )}}}} & (4)\end{matrix}$

In the expression (1), x and v denote the coordinates (x, y) indicatinga pixel position of the output images from the demosaic and noisereduction filters 221, 222 and 223; px and py denote the coordinates(px, py) indicating a pixel position of an input image; and W denotes aweighting factor indicating the weight of the filter.

The weight [t] of the filter is calculated by a product of thespace-dependent weight [Ws] dependent upon pixel coordinates and theedge-dependent weight [Wr] dependent upon the strength of an edge of theimage, as shown in the expression (1).

The space-dependent weight [Ws] is expressed by the above expression(2). The edge-dependent weight [Wr] is expressed by the aboveexpressions (3a) and (3b). In the expressions, as denotes the standarddeviation of the pixel value of a pixel having a pixel value included inan input mosaic image of any of R, G and B that is a processing object;or is the standard deviation of the pixel value of the edge evaluatingimage 212, which is the A channel demosaic image obtained by the linearinterpolating processing of an A mosaic image; and in (px, py) denotesthe pixel value at the pixel position (px, py).

The space-dependent weight [Ws] is calculated by applying the distancesbetween the pixel position (x, y) and the surrounding pixel positions(px, py), and the standard deviation as in accordance with the aboveexpression (2).

On the other hand, the edge-dependent Weight [Wr] is calculated byapplying the pixel value Edge(x, y) at the pixel position (x, y) in theedge evaluating image 212, the pixel values Edge(px, py) at thesurrounding pixel positions (px, py) and the standard deviation or inaccordance with the above expressions (3a) and (3b). It is noted that,because the processing object image is an RGB mosaic image, there aresurrounding pixels in which pixel values exist [In (px, py) exists] andsurrounding pixels in which no pixel values exist [In (px, py) doesn'texists].

The edge-dependent weights [Wr] at the surrounding pixel positions (px,py) in which the pixel values exist are calculated in accordance withthe above expression (3a), and the edge-dependent weights [Wr] at thesurrounding pixel positions (px, py) in which no pixel values exist arecalculated in accordance with the above expression (3b) to be 0regardless of the pixel values Edge(px, py).

The edge-dependent weights [Wr] dependent upon the strength of edges arethe weights calculated by applying the pixel values of the edgeevaluating image 212. When the differences between the pixel valueEdge(x, y) at the pixel position (x, y) and the pixel values Edge(px,py) at the surrounding pixel positions (px, py) are small, theedge-dependent weights [Wr] are set to be large. When the differencesare large, the edge-dependent weights [Wr] are set to be small. Bysetting the weights of the pixels having large differences to be smallin such a way, an effect of suppressing the occurrence of noise can beobtained.

The space-dependent weight [Ws] and the edge-dependent weight [Wr] arecalculated with regard to each of the surrounding pixel positions (px,py) of the pixel position (x, y) on the basis of the above expressions(2), (3a) and (3b), and an overall weight W is calculated in accordancewith the above expression (1) by applying the space-dependent weight[Ws] and the edge-dependent weight [Wr]. In addition, for example, the7×7 surrounding pixels are applied as the surrounding pixels used in thefiltering processing, as described above with reference to FIG. 12.

The calculation of the output pixel value [Out(x, y)] at the pixelposition (x, y) is executed in conformity to the above expression (4)after the determination of the weights [W=Ws·Wr] of the surroundingpixels. The output pixel value [Out(x, y)] at the pixel position (x, y)is a value obtained by normalizing the convolution of the weights [W]and the pixel values [In(px, py)] at the surrounding pixels in the inputimage by the summation of the weights. Because the weights [W] become 0at the pixels in which the pixel values In(px, py) do not exist, thefactors are calculated only to the pixels existing in the channels towhich the present filters are applied, and the pixel values as theresult of the multiplication by them are calculated.

As described above, because the demosaic and noise reduction filters221, 222 and 223 are configured to calculate the output pixel value[Out(x, y)] at the pixel position (x, y) by applying the weight [W]calculated by the product of the space-dependent weight (Ws) dependentupon the pixel coordinates and the edge-dependent weight [Wr] dependentupon the strength of the edges of an image calculated in conformity withthe edge evaluating image 212 generated on the basis of the A-channelimage, the demosaic processing and the noise reduction processing can beperformed at the same time.

As shown in FIG. 11, also to the A-channel mosaic image included in thecorrected mosaic image 211, similarly to the RGB mosaic image, the edgepreserving processing of the A-mosaic image is performed in an edgepreserving filter 224 on the basis of the edges appearing in the edgeevaluating image 212, which is the A-channel demosaic image. Theprocessing applies the above expressions (1)-(4) to execute theprocessing of generating a noise reduced demosaic image based on theA-mosaic image.

The A-channel noise-reduced demosaic image generated by the edgepreserving filter 224 is input into an FIT high pass filter 226, and theextraction processing of high frequency components is executed togenerate an HPF result image 214. The FIT high pass filter 226 is an FITfilter for extracting the high frequency components. An example of thefactors of the FIT high pass filter 226 is shown in FIG. 13.

The HPF result image 214 is further input into a gain control processingunit 227, and the gain of the image 214 is adjusted, or amplified.Furthermore, the gain-adjusted image receives the execution of a matrixoperation in a matrix operation executing unit 228, and R, G and B dataincluded in the edge portion data in the A-channel image is extracted.Then, the extracted R, G and B data receives the addition processingwith a noise-reduced RGB demosaic image 213 in a synthesis processingexecuting unit 229, and thereby an output RGB image 215 is generated tobe output.

In addition, the data generated by the gain control and the matrixoperation of the HPF result image 214 generated by the high frequencycomponent extraction from the A-channel noise-reduced demosaic imagegenerated by the edge preserving filter 224 is the image data applied toedge portion emphasizing processing, and the output RGB image 215, inwhich the edge portions are emphasized, can be obtained by adding thedata with the noise-reduced RGB demosaic image 213 in the synthesisprocessing executing unit 229.

[4. Third Image Signal Processing Example]

Next, a third image signal processing example of the present inventionis described with reference to FIG. 14. The processing configurationshown in FIG. 14 includes the configuration for executing color spaceconversion processing. The processing until the acquisition of an RGBdemosaic image 311 and an A-demosaic image 312 by the processing from animager 301 to a demosaic processing unit 303 is the processing similarto the first processing example described above with reference to FIG.7. In the present third processing example, the data after the noisereduction processing of the RGB demosaic image 311 and the A-demosaicimage 312 is multiplied by a color space converting matrix in a matrixoperation executing unit 306, and an output RGB image 315 and anestimated infrared (IR) image 316 are obtained.

The present processing example is now described. The imager 301 is animager of R, G, B and A described with reference to FIG. 6, and iscomposed of the filter having four kinds of spectral characteristics ofR, G, B and A. The four kinds of spectra are composed of an R channel, aG channel, a B channel and an A channel transmitting all of infraredrays (IR), R, G and B.

An image photographed by the imager 301 becomes a mosaic image composedof the four kinds of spectra. The mosaic image is composed of four kindsof mosaic images composed of each of the R, G, B and A channels, asshown in FIG. 8A. These mosaic images are input into a white balanceprocessing unit 302.

The white balance processing unit 302 executes the white balancecorrecting processing for equalizing the ranges of the pixel valuesincluded in the mosaic images having the four kinds of differentspectral characteristics to be almost the same. The correction ofequalizing the ranges of the pixel values of the pixels included in eachof the mosaic images having different spectral characteristics from oneanother to be almost the same is performed to the values of the pixelsconstituting the mosaic images by the white balance adjustingprocessing, and corrected mosaic images are obtained. The arrays of thepixels of the four mosaic images are as shown in FIG. 8A.

The demosaic processing of these four mosaic images is executed at ademosaic processing unit 303, subsequently, and the RGB demosaic image311 and the A-demosaic image 312 are obtained. The demosaic processingis performed by the processing of setting the pixel values of all thepixels having no pixel values by executing the interpolation based onthe pixel values of the surrounding pixels, as described above withreference to FIG. 3. For example, a method similar to the well-knownVargra algorithm can be applied. By the demosaic processing of thedemosaic processing unit 303, four demosaic images shown in FIG. 8B canbe obtained.

The RGB demosaic image 311 and the A-demosaic image 312 that have beenobtained in such a way are input into noise reduction processing units304 and 305, respectively, and noise reduction processing is executed.The noise reduction processing, unit 304 is a noise reduction processingunit having a configuration as described with reference to FIG. 9 in theprevious first processing example. The noise reduction processing unit305 is a noise reduction processing unit composed of a general bilateralfilter and the like. The noise reduction processing units 304 and 305output a noise-reduced RGB demosaic image 313 and a noise-reduced Ademosaic image 314 as the noise reduction processing results,respectively.

The matrix operation executing unit 306 considers the four pixel values(R, G, B and A) per pixel that can be obtained from these poise-reducedimages 313 and 314 as a vector, and multiplies the four pixel values bythe color space converting matrix to obtain the output RGB image 315 andthe estimated IR image 316 as a result.

The converting matrix applied in the matrix operation executing unit 306is a four-dimensional color space converting matrix evaluating the colorreproducibility of the output RGB image 315 as a conversion result onthe basis of the color difference with a color patch, the differenceswith the pixel values of R, G, B and IR of a gray patch, and the like onthe assumption that the R, G and B channels include the leakage of aninfrared (IR) light, and then obtaining a matrix that optimized thereproducibility as a group of numerical values. Examples of concreteconverting matrices are shown in the following.

$\begin{matrix}{\mspace{79mu}{\begin{bmatrix}R \\G \\B \\A\end{bmatrix} = {\begin{bmatrix}1.0 & 0.0 & 0.0 & 0.27 \\0.0 & 1.1 & 0.0 & 0.13 \\0.0 & 0.0 & 1.0 & 0.09 \\0.299 & 0.597 & 0.114 & 0.50\end{bmatrix}\begin{bmatrix}R_{ideal} \\G_{ideal} \\B_{ideal} \\{IR}_{ideal}\end{bmatrix}}}} & (5) \\{\begin{bmatrix}R_{out} \\G_{out} \\B_{out} \\{IR}_{out}\end{bmatrix} = {\begin{bmatrix}1.243603 & 0.486391 & 0.092879 & {- 0.81473} \\0.117290 & 1.234188 & 0.044719 & {- 0.39228} \\0.081201 & 0.16213 & 1.03096 & {- 0.27158} \\{- 0.90223} & {- 1.80145} & {- 0.344} & 3.017502\end{bmatrix}\begin{bmatrix}R_{in} \\G_{in} \\B_{in} \\A_{in}\end{bmatrix}}} & (6)\end{matrix}$

The expression (5) is a determinant indicating the spectralcharacteristics of the imager to which the present processing example isapplied, i.e., the spectral characteristics of each of the channelsincluding the R, G, B and A channels shown in FIG. 6, and shows that theoptical component obtained from the R channel includes 0 of G and Bcomponents and 27 of an infrared (IR) component to 100 of the ideal Rcomponent. The G channel includes 0 of the R and B components and 13 ofthe infrared (IR) component to 100 of the ideal G component. The Bchannel is composed of 0 of the R and B components and 9 of the infrared(IR) component to 100 of the ideal B component. Furthermore, the Achannel is composed of 29.9 of the R component, 59.7 of the G component,11.4 of the B component, and 50 of the infrared (IR) component.

The above expression (6) is a color space converting matrixcorresponding to such an imager. Rin, Gin, Bin and Ain correspond tofour pixel values (Rin, Gin, Bin, Ain) per pixel that can be obtainedfrom the noise-reduced images 313 and 314. The matrix operation shown inthe above expression (6) is executed to the pixel values (Rin, Gin, Bin,Ain) to obtain output values (Rout, Gout, Bout, Aout).

The output values (Rout, Gout, Bout) among the output values (Rout,Gout, Bout, Aout) correspond to the image composed of ‘only’ the R, Gand B components obtained by removing the infrared component from thenoise-reduced RGB demosaic image 313 and the noise-reduced A-demosaicimage 314, and the output values (Rout, Gout, Bout) are set as theoutput RGB image 315. Moreover, the output value Aout among the outputvalues (Rout, Gout, Bout, Aout) corresponds to the image composed ofonly the infrared component that does not include the R, G and Bcomponents and has been extracted from the noise-reduced RGB demosaicimage 313 and the noise-reduced A-demosaic image 314, and the outputvalue Aout is output as the estimated IR image 316.

According to the processing example, it is possible to obtain a highquality image from which the infrared component that has passed throughthe RGB elements of the imager has been removed. That is, in the RGBAimager that has been described with reference to FIG. 6, the infrared(IR) components are included in the optical components that have passedthrough the RGB elements, but it becomes possible to obtain a highquality RGB image by analyzing the passing components of the A-channelsand by applying the matrix operation to remove the IR components fromthe optical components that have passed through the RGB elements.

[5. Fourth Image Signal Processing Example]

Next, a fourth image signal processing example of the present inventionis described with reference to FIGS. 15 and 16. In the processingconfiguration shown in FIG. 15, the processing up to obtaining acorrected mosaic image 411 including four mosaic images of R, G, B and Ais similar to that of the fourth processing example described above withreference to FIG. 14. That is, an imager 401 is the imager of R, G, Band A, which has been described with reference to FIG. 6, and iscomposed of a filter having four kinds of spectral characteristics of R,G, B and A. The four kinds of spectra are composed of an R channel, a Gchannel, a B channel and an A channel transmitting all of the infraredrays (IR), the R, the G and the B.

In the present fourth example, demosaic processing, noise reductionprocessing and infrared (IR) calculation processing are executed as anintegrated filtering algorithm on the basis of the corrected mosaicimage 411 including, four mosaic images of R, G, B and A, and an outputRGB image 412 and an estimated IR image 413 are obtained.

An image photographed by the imager 401 becomes a mosaic image composedof four kinds of spectra. The mosaic image is composed of the four kindsof mosaic images composed of each of the R, G, B and A channels, asshown in FIG. 8A. These mosaic images are input into a white balanceprocessing unit 402.

The white balance processing unit 402 executes the white balancecorrecting processing of equalizing the ranges of the pixel valuesincluded in the mosaic images having the four kinds of differentspectral characteristics to be almost the same. The correction ofequalizing the ranges of the values of the pixels included in each ofthe mosaic images having different spectral characteristics from oneanother to be almost the same is performed to the values of the pixelsconstituting the mosaic images by the white balance adjustingprocessing, and corrected mosaic images are obtained. The arrays of thepixels of the four mosaic images are as shown in FIG. 8A.

Next, a demosaic & noise reduction & IR calculation processing unit 404executes the demosaic processing, the noise reduction processing and theinfrared (IR) calculation processing of these four mosaic images as theintegrated filtering algorithm on the basis of the corrected mosaicimage 411 including the four mosaic images of R, G, B and A, and outputsthe output RGB image 412 and the estimated IR image 413.

The configuration and the processing of the demosaic & noise reduction &IR calculation processing unit 404 are described with reference to FIG.16. The configuration shown in FIG. 16 is similar to that of thedemosaic & noise reduction processing unit 204, which has been describedabove with reference to FIG. 11 in the second processing example.Difference from the configuration of the demosaic & noise reductionprocessing unit 204 is that a matrix operation executing unit 429 isadded. The demosaic & noise reduction & IR calculation processing unit404 is configured to separate and output the output RGB image 412 andthe estimated IR image 413 by a matrix operation in the matrix operationexecuting unit 429.

Demosaic and noise reduction filters 421, 422 and 423 perform the imageprocessing by the edge preserving filters for reducing noise whilepreserving the edges to the mosaic images of R, G and B included in themosaic image (including R, G, B and A) 411, which is an corrected mosaicimage, respectively, and execute demosaic processing to obtain anoise-reduced RGB demosaic image 451, similarly to the second processingexample, which has been described above with reference to FIG. 11.

For the noise reduction processing, an edge evaluating image 450generated by the processing in a linear demosaic filter 425 is appliedto the A-mosaic image, and thereby the image processing by the edgepreserving filter for reducing noise with the edges of an original imagethat are located at the same positions where the edges appearing in theedge evaluating image 450 being preserved is performed. The processingis the processing that has been described above with reference to FIG.12, and is the processing in which the above expressions (1) to (4) areapplied, namely the processing of calculating the output pixel value[Out(x, y)] at the pixel position (x, y) by applying the weight [W]calculated by the product of the space-dependent weight [Ws] dependentupon the pixel coordinates and the edge-dependent weight [Wr] dependentupon the strength of the edges of an image calculated in conformity tothe edge evaluating image 450 generated on the basis of the A-channelimage. By the processing, demosaic processing and noise reductionprocessing can be performed at the same time.

Similarly to the second processing example, the edge preservingprocessing of the A-mosaic image is performed in an edge preservingfilter 424 also to the A channel mosaic image included in the correctedmosaic image 411 similarly to the RGB mosaic image on the basis of theedges appearing in the edge evaluating image 450, which is the A-channeldemosaic image. The processing also applies the above expressions(1)-(4) to be executed as the processing of generating a noise-reducedA-demosaic image 452 based on the A-mosaic image.

The noise-reduced A-demosaic image 452 generated by the edge preservingfilter 424 is input into an FIT high pass filter 426, and the extractionprocessing of high frequency components is executed to generate an HPFresult image 414. The FIT high pass filter 426 is an FIT filter forextracting the high frequency components, and has the factors describedabove with reference to FIG. 13, for example.

The HPF result image 414 is further input into a gain control processingunit 427, and the gain of the image 414 is adjusted, or amplified.Furthermore, the gain-adjusted image receives the execution of a matrixoperation in a matrix operation executing unit 428, and R, G and B dataincluded in the edge portion data in the A-channel image is extracted tobe output to a synthesis processing executing unit 430.

Furthermore, in the present fourth processing example, the noise-reducedA-demosaic image 452 corresponding to the A-channel generated in theedge preserving filter 424 and the noise-reduced RGB demosaic image 451generated by the processing of the demosaic and noise reduction filters421, 422 and 423 are input into the matrix operation executing unit 429,and a matrix operation based on the input information is executed.

The matrix operation in the matrix operation executing unit 429 is aprocessing similar to the processing in the matrix operation executingunit 306, which processing has been described with reference to FIG. 14in the third processing example. The matrix operation executing unit 429regards four pixel values (R, G, B and A) per pixel as a vector, whichfour pixel values are obtained from the noise-reduced A-demosaic image452 generated in the edge preserving filter 424 and the noise-reducedRGB demosaic image 451, and multiplies the four pixel values by thecolor space converting matrix. As a result, the matrix operationexecuting unit 429 obtains an RGB image to be input into the synthesisprocessing executing unit 430 and the estimated IR image 413, andoutputs the images.

The converting matrix applied in the matrix operation executing unit 429is a four-dimensional color space converting matrix evaluating the colorreproducibility of the RGB image as a conversion result on the basis ofthe color difference with a color patch, the differences with the pixelvalues of R, G, B and IR of a gray patch, and the like on the assumptionthat the R, G and B channels include the leakage of an IR light, andthen obtaining a matrix that makes the reproducibility the best asnumeral values. As a concrete converting matrix, for example, theexpression (6) described above in the third processing example isapplied.

The matrix operation executing unit 429 executes the matrix operationexpressed by the expression (6) described above to obtain output values(Rout, Gout, Bout and Aout). The output values (Rout, Gout and Bout)among the output values (Rout, Gout, Bout and Aout) correspond to theimage composed of only the R, G and B components generated by removingthe IR components from the noise-reduced RGB demosaic image 451 and thenoise-reduced A-demosaic image 452, and the output values (Rout, Goutand Bout) are set to the RGB image to be input into the synthesisprocessing executing unit 430.

Moreover, the output value (Aout) among the output values (Rout, Gout,Bout and Aout) corresponds to the image that has been generated from thenoise-reduced RGB demosaic image 451 and the noise-reduced A-demosaicimage 452 and does not include the R, G and B components and is composedof only the IR component, and the output value (Aout) is output as theestimated IR image 413.

The synthesis processing executing unit 430 executes the additionprocessing of the image that has been generated by removing the IRcomponents generated by the matrix operation of the matrix operationexecuting unit 429 to be composed of only the R, G and B components, andthe extracted data of the R, G and B data included in the edge portiondata generated on the basis of the A-channel image in the matrixoperation executing unit 428 to generate and output the output RGB image412. In the synthesis processing executing unit 430, the output RGBimage 412 whose edge portions are emphasized can be obtained.

In the above, the present invention has been described in detail,referring to the specific embodiment. However, it is apparent that theskilled person in the art can perform modifications and thesubstitutions of the embodiment without departing from the spirit of thepresent invention. That is, the present invention has been disclosed inthe form of an illustration, and the present invention should not beinterpreted to be limited to the embodiment. In order to judge the scopeof the present invention, the claims should be taken into consideration.

Moreover, a series of processing described in the present specificationcan be executed by hardware, software or a compound configuration ofboth of them. In the case of executing the processing by software, aprogram recording a processing sequence can be installed in a memory ina computer built in exclusive hardware to be executed, or the programcan be installed in a general purpose computer capable executing variouskinds of processing to be executed.

For example, the program can be recorded in advance into a hard disk ora read only memory (ROM) as a recording medium. Alternatively, theprogram can be temporarily or eternally stored (recorded) into aremovable recording medium such as a flexible disk, a compact disc readonly memory (CD-ROM), a magneto optical (MO) disk, a digital versatiledisc (DVD), a magnetic disc, a semiconductor memory or the like. Such aremovable recording medium can be provided as the so called packagesoftware.

In addition, the program can be wirelessly transferred to a computerfrom a download site, or can be transferred to a computer by wirethrough a network such as a local area network (LAN), the Internet orthe like, in addition to the installation into a computer from theremovable recording medium mentioned above, and the computer can receivethe program transferred in the way mentioned above to install thereceived program into a recording medium such as a hard disk built inthe computer.

In addition, the various kinds of processing described in the presentspecification are not only sequentially executed in conformity to thedescriptions, but also can be executed in parallel or severallyaccording to the throughput of an apparatus executing the processing oron occasion. Moreover, the system in the present specification indicatesthe logical set configuration of a plurality of apparatus, and thesystem is not limited to one in which the apparatus of eachconfiguration is in the same housing.

As described above, according to the configuration of the presentinvention, the demosaic image of each of the obtained signals isgenerated based on the mosaic image data of each of the signals obtainedby a single plate imager including an element array composed of thevisible light obtaining elements obtaining the visible light signalssuch as R, G and B signals and the invisible light obtaining elementsobtaining the signals including the invisible light components includinginfrared rays and the like, and the correction of the pixel values ofthe demosaic image obtained by the visible light obtaining elements isexecuted based on the edge information extracted from the demosaic imageof the signals obtained by the invisible light obtaining elements.Thereby, the high quality image data including reduced noise can beobtained based on an image obtained by one time of photographingprocessing.

It should be understood by those skilled, in the art that variousmodifications, combinations, sub-combinations and alterations may occurdepending on design requirements and other factors insofar as they arewithin the scope of the appended claims or the equivalents thereof.

CROSS REFERENCES TO RELATED APPLICATIONS

The present document contains subject matter related to Japanese PatentApplication JP 2005-7369378 filed in the Japanese Patent Office on Dec.22, 2005, the entire contents of which being incorporated herein byreference.

What is claimed is:
 1. An image signal processing apparatus, comprising:a noise reduction processing unit that: establishes weights for firstpixel values of a first demosaic image based on edge informationextracted from a second demosaic image; generates second pixel valuesfor the first demosaic image based on an application of the establishedweights to corresponding ones of the first pixel values; a speculumdetecting unit that establishes an evaluation result based ondifferences in the second pixel values and differences in third pixelvalues of the second demosaic image; a first blend execution unit thatgenerates output image data based on the evaluation result and a productof the second pixel values and fourth pixel values generated through anapplication of a filter to the third pixel values; and a second blendexecution unit generating visible output image data based on theevaluation result and the generated output image data.
 2. The imagesignal processing apparatus of claim 1, wherein the second blendexecution unit determines whether the evaluation result represents afirst type of result.
 3. The image signal processing apparatus of claim2, wherein: the image processing apparatus further comprises a filterunit that generates fifth pixel values based on an application of afilter to the first pixel values; and the second blend execution unitenlarges at least one of the fifth pixel values to generate at least aportion of the visible output image data, when the evaluation result isdetermined to represent the first type.
 4. The image signal processingapparatus of claim 2, wherein the second blend execution unit enlarges apixel value included in the output image data to generate at least aportion of the visible output image data, when the evaluation result isdetermined not to represent the first type.
 5. The image signalprocessing apparatus of claim 1, wherein the at least a portion of thedifferences in the second and third pixel values result from a change inillumination.
 6. The image signal processing apparatus of claim 1,further comprising a demosaic processing unit that: receives input ofmosaic image data based on signals obtained by an imaging device havingan element array including a first element and a second element, thefirst element being a visible light obtaining element, and the secondelement being an invisible light obtaining element; generates a firstdemosaic image corresponding to a first subset of the signals obtainedby the visible light signal obtaining element; and generates a seconddemosaic image corresponding to a second subset of the signals obtainedby the invisible light obtaining element.
 7. The image signal processingapparatus of claim 6, wherein the first and second subsets of thesignals are obtained simultaneously during capturing of an image by theimaging device.
 8. The image signal processing apparatus of claim 6,wherein: the visible light obtaining element includes RGB elementsobtaining R, G, and B color signals to generate the first demosaicimage; and the invisible light obtaining element includes A elementsobtaining an A signal, the A signal including R, G, B, and infraredcomponents.
 9. The image signal processing apparatus of claim 8, whereinthe noise reduction processing unit corrects at least one of the firstpixel values based on the A signal.
 10. The image signal processingapparatus of claim 1, further comprising: an imaging device having acolor array composed of RGB elements and A elements, the RGB elementsbeing visible light obtaining elements, and the A elements beinginvisible light obtaining elements, wherein the color array obtains R,G, and B color signals and A signals simultaneously during capturing ofan image; and a demosaic processing unit generating a first demosaicimage based on the R, G, and B color signals obtained by the RGBelements, and generating a second demosaic image based on the A signalsobtained by the A elements.
 11. A method, comprising: establishing,using at least one processor, weights for first pixel values of a firstdemosaic image based on edge information extracted from a seconddemosaic image; generating, using the at least one processor, secondpixel values for the first demosaic image based on an application of theestablished weights to corresponding ones of the first pixel values;establishing, using the at least one processor, an evaluation resultbased on differences in the second pixel values and differences in thirdpixel values of the second demosaic image; generating, using the atleast one processor, output image data based on the evaluation resultand a product of the second pixel values and fourth pixel values, thefourth pixel values being generated through an application of a filterto the third pixel values; and generating, using the at least oneprocessor, visible output image data based on the evaluation result andthe generated output image data.
 12. The method of claim 11, furthercomprising determining whether the evaluation result represents a firsttype of result.
 13. The method of claim 12, wherein: the method furthercomprises generating fifth pixel values based on an application of afilter to the first pixel values; and generating the visible outputimage data comprises generating at least a portion of the visible outputimage data by enlarging at least one of the fifth pixel values, when theevaluation result is determined to represent the first type.
 14. Themethod of claim 12, wherein generating the visible output image datacomprises generating at least a portion of the visible output image databy enlarging a pixel value included in the output image data, when theevaluation result is determined not to represent the first type.
 15. Themethod of claim 11, wherein the at least a portion of the differences inthe second and third pixel values result from a change in illumination.16. The method of claim 11, further comprising receiving mosaic imagedata, the mosaic image data comprising signals obtained by an imagingdevice having an element array including a first element and a secondelement, the first element being a visible light obtaining element, andthe second element being an invisible light obtaining element.
 17. Themethod of claim 16, further comprising: generating a first demosaicimage corresponding to a first subset of the signals obtained by thevisible light signal obtaining element; and generating a second demosaicimage corresponding to a second subset of the signals obtained by theinvisible light obtaining element.
 18. The method of claim 17, wherein:the first subset of the signals comprises R, G, and B color signalsobtained by one or more RGB elements of the visible light obtainingelement; and the second subset of the signals comprises an A signalobtained by one or more A elements of the invisible light obtainingelement, the A signal comprising including R, G, B, and infraredcomponents.
 19. The method of claim 18, further comprising correcting atleast one of the first pixel values based on the A signal.
 20. Anon-transitory computer-readable storage medium storing a computerprogram that, when executed on a processor of an imaging apparatus,causes the processor to perform a method for image signal processing,the method comprising: establishing weights for first pixel values of afirst demosaic image based on edge information extracted from a seconddemosaic image; generating second pixel values for the first demosaicimage based on an application of the established weights tocorresponding ones of the first pixel values; establishing an evaluationresult based on differences in the second pixel values and differencesin third pixel values of the second demosaic image; generating outputimage data based on the evaluation result and a product of the secondpixel values and fourth pixel values, the fourth pixel values beinggenerated through an application of a filter to the third pixel values;and generating visible output image data based on the evaluation resultand the generated output image data.